An Efficient Algorithm for Recognition of Human Actions

An Efficient Algorithm for Recognition of Human Actions

Recognition of human actions is an emerging need. Various researchers have endeavored to provide a solution to this problem. Some of the current state-of-the-art solutions are either inaccurate or computationally intensive while others require human intervention. In this paper a sufficiently accurat...

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Main Authors: Yaser Daanial Khan, Nabeel Sabir Khan, Shoaib Farooq, Adnan Abid, Sher Afzal Khan, Farooq Ahmad, M. Khalid Mahmood
Format: Article
Language:English
Published: Hindawi Limited 2014-01-01
Series:The Scientific World Journal
Online Access:http://dx.doi.org/10.1155/2014/875879
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spelling doaj-7d61fb5d78554ef196fe9f7582f1f7702020-11-25T00:11:18ZengHindawi LimitedThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/875879875879An Efficient Algorithm for Recognition of Human ActionsYaser Daanial Khan0Nabeel Sabir Khan1Shoaib Farooq2Adnan Abid3Sher Afzal Khan4Farooq Ahmad5M. Khalid Mahmood6School of Science and Technology, University of Management and Technology, Lahore 54000, PakistanSchool of Science and Technology, University of Management and Technology, Lahore 54000, PakistanSchool of Science and Technology, University of Management and Technology, Lahore 54000, PakistanSchool of Science and Technology, University of Management and Technology, Lahore 54000, PakistanDepartment of Computer Science, Abdul Wali Khan University, Mardan 23200, PakistanFaculty of Information Technology, University of Central Punjab, 1-Khayaban-e-Jinnah Road, Johar Town, Lahore 54000, PakistanDepartment of Mathematics, University of the Punjab, Lahore 54000, PakistanRecognition of human actions is an emerging need. Various researchers have endeavored to provide a solution to this problem. Some of the current state-of-the-art solutions are either inaccurate or computationally intensive while others require human intervention. In this paper a sufficiently accurate while computationally inexpensive solution is provided for the same problem. Image moments which are translation, rotation, and scale invariant are computed for a frame. A dynamic neural network is used to identify the patterns within the stream of image moments and hence recognize actions. Experiments show that the proposed model performs better than other competitive models.http://dx.doi.org/10.1155/2014/875879
collection DOAJ
language English
format Article
sources DOAJ
author Yaser Daanial Khan
Nabeel Sabir Khan
Shoaib Farooq
Adnan Abid
Sher Afzal Khan
Farooq Ahmad
M. Khalid Mahmood
spellingShingle Yaser Daanial Khan
Nabeel Sabir Khan
Shoaib Farooq
Adnan Abid
Sher Afzal Khan
Farooq Ahmad
M. Khalid Mahmood
An Efficient Algorithm for Recognition of Human Actions
The Scientific World Journal
author_facet Yaser Daanial Khan
Nabeel Sabir Khan
Shoaib Farooq
Adnan Abid
Sher Afzal Khan
Farooq Ahmad
M. Khalid Mahmood
author_sort Yaser Daanial Khan
title An Efficient Algorithm for Recognition of Human Actions
title_short An Efficient Algorithm for Recognition of Human Actions
title_full An Efficient Algorithm for Recognition of Human Actions
title_fullStr An Efficient Algorithm for Recognition of Human Actions
title_full_unstemmed An Efficient Algorithm for Recognition of Human Actions
title_sort efficient algorithm for recognition of human actions
publisher Hindawi Limited
series The Scientific World Journal
issn 2356-6140
1537-744X
publishDate 2014-01-01
description Recognition of human actions is an emerging need. Various researchers have endeavored to provide a solution to this problem. Some of the current state-of-the-art solutions are either inaccurate or computationally intensive while others require human intervention. In this paper a sufficiently accurate while computationally inexpensive solution is provided for the same problem. Image moments which are translation, rotation, and scale invariant are computed for a frame. A dynamic neural network is used to identify the patterns within the stream of image moments and hence recognize actions. Experiments show that the proposed model performs better than other competitive models.
url http://dx.doi.org/10.1155/2014/875879
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